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Record W4295898342 · doi:10.1186/s40900-022-00386-2

Stroke survivors partner in research: a case example of collaborative processes

2022· letter· en· W4295898342 on OpenAlexaffabout
Alyson Kwok, Deacon Cheung, Maysyn Gordon, Evan Mudryk, Patricia J. Manns

Bibliographic record

VenueResearch Involvement and Engagement · 2022
Typeletter
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsGlenrose Rehabilitation HospitalUniversity of Alberta
Fundersnot available
KeywordsThematic analysisInclusion (mineral)Qualitative researchPsychologyValue (mathematics)Process (computing)Medical educationPatient participationKnowledge managementMedicineSocial psychologyHealth careSociologyComputer science

Abstract

fetched live from OpenAlex

The Canadian Strategy for Patient-Oriented Research supports the inclusion of patients as partners throughout the research process. Purposeful and meaningful engagement of patient partners after stroke can present unique challenges due to the potential impacts on cognition, communication, or mobility. The purpose of this paper is to provide a case example of working together with three individuals who bring their post-stroke lived experience, including one person with aphasia, from study design through to dissemination. The designed and executed qualitative research was the purpose of this collaboration; this paper describes the collaborative process rather than the outcomes of the original research. The Strategy for Patient-Oriented Research Patient Engagement Framework was followed to engage the patient partners fully as part of the research team. Patient partners were involved at regularly scheduled team meetings and provided guidance on key aspects of project design and decision-making. The patient partners provided robust and important contributions to many aspects of the research, including shaping interview questions, assisting with thematic analysis, and contributing to the dissemination of research findings. Effective team dynamics were fostered by focusing on the value of the lived experience knowledge, using best-practice communication strategies, as well as taking time for relationship-building and story sharing. With appropriate support and guidance, the individuals who have experienced stroke were valuable contributing members of our research team.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.042
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0420.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.013
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.798
GPT teacher head0.570
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2022
Admission routes2
Has abstractyes

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